Thermodynamic Modelling and Simulation for High Efficiency Design and Operation of Geothermal Power Plants

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Thesis Discipline

Mechanical Engineering

Degree Grantor

University of Canterbury

Degree Level

Doctoral

Degree Name

Doctor of Philosophy

This thesis analyses long term and short term environmental effects on geothermal power plant performance and discusses adaptive ways to improve performance. Mokai 1 geothermal power plant has been used as a case study for this investigation. Mokai 1 is a combined cycle plant where the binary cycles are air-cooled. The plant performance of an air-cooled binary cycle geothermal power plant is dependent on the environment (resource characteristics as well as weather conditions). For modelling such a power plant, two time scales are of interest: the yearly basis for aggregate plant performance for design and operations; and the daily basis for hourly plant performances for an accurate dispatch prediction.

Adaptive methodology for long term performance improvement has been introduced in this work which would save money and effort in the future by keeping the provisions to adapt to changes in resource characteristics based on geothermal reservoir modelling. The investigation was carried out using a steady state computer simulator of Mokai 1 geothermal power plant. The steady sate simulator was built specifically for this work. The deviation in performance of various components is less than 5% compared to the original plant design. The model is very generic and it can be used for other plants with simple adaptation or can be used for future plant design.

One of the main contributions of this work is an iterative method for modelling the environmental effect on short term performance on the air-cooled organic Rankine cycle. The ambient temperature is identified as the most influencing parameter on short term performance which influences the performance of the whole cycle in two ways. Firstly, by changing the equilibrium pressure inside the condenser, the turbine outlet pressure changes and hence, the turbine pressure ratio also changes. The turbine pressure ratio is a major parameter determining power generated by a turbine; therefore, the plant output is affected. Secondly, by changing the condenser outlet temperature with the ambient temperature, the pump inlet and outlet condition and consequently vaporizer equilibrium temperature and pressure are influenced. The developed method sought the equilibrium conditions of both condenser and vaporizer iteratively. In short, ORC cycle shifts on the T-s plane depending on the ambient temperature. This method iteratively seeks the shifted ORC on the T,s plane.

Two case studies have been carried out to demonstrate the method. The developed method shows robustness and converges exponentially. The model is effective for cycles that use saturated vapour as well as superheated vapour. The model essentially assumes steady state operation of the power cycle. The possible unit time where this model can be applied is bounded by the time required by a system to come into steady state. The saturated vapour cycle yielded average error 4.20% with maximum error 9.25% and the superheated vapour cycle yielded average error 2.12% with maximum error 5.60%. The main advantage of the developed method is that it requires a minimum number of inputs: condenser (p,T), vaporizer (p,T), condenser heat load, turbine efficiency (overall), pump work and the extremum conditions of all the components. These inputs should represent typical operating conditions of a plant. The model can predict the appropriate plant performance depending on the system heat input (geothermal fluid flow in this case) and the heat sink temperature. As the method is based on basic thermodynamics rather than empirical or semi-empirical approaches, this method is widely applicable. The main focus of this work is on the ORC but the developed method is applicable to any closed Rankine cycle. In addition, application of the developed iterative method to predict plant performance based on mean yearly weather data is also discussed in the thesis.

Water-augmented cooling system and optimization of plant operating point parameters have been proposed as adaptive measures to improve short term performance. Developed iterative method has been used for the short term performance analysis. The water-augmented cooling system is specifically suitable to mitigate the reduced power output during the summer. The simulated average gain in power during the summer (Jan, Feb, Nov and Dec) of an ORC of Mokai 1 geothermal power plant by incorporating a water-augmented cooling system was 2.3% and the average gain for the whole year was 1.6% based on the weather data of Taupo for the year 2005. A cost benefit analysis showed that water-augmented cooling system is more economical compared to other alternative renewable energies considered to meet summer peak demand. From the green house gas emissions perspective, water-augmented cooling is a better option than the gas fired peaking plants.

Adaptive approach for short term performance improvement by optimizing operating point parameters of an air-cooled binary cycle has huge potential with possible maximum improvement in power output by about 50%. The optimization takes in to account the effects of the geothermal resource characteristics and the weather conditions. The optimization is achieved by manipulating cycle mass flow rate and vaporizer equilibrium condition. Further study on the optimizing operating points to achieve improved short term performance has been recommended for future work.